docs: def plot_corner(sampler, show_ML=True, **kwargs):
      """
      A plot that summarizes the parameter samples by showing them as individual
      histograms and 2D histograms against each other. The maximum likelihood
      parameter vector is indicated by a cross.
  
      This function is a thin wrapper around `corner.corner`, found at
      https://github.com/corner/corner.py.
  
      Parameters
      ----------
      sampler : `emcee.EnsembleSampler`
          Sampler with a stored chain.
      show_ML : bool, optional
          Whether to show the maximum likelihood parameter vector as a cross on
          the 2D histograms.
      """
      import matplotlib.pyplot as plt
  
      oldlw = plt.rcParams["lines.linewidth"]
      plt.rcParams["lines.linewidth"] = 0.7
      try:
          from corner import corner
  
          if show_ML:
              _, MLp, _, _ = find_ML(sampler, 0)
          else:
              MLp = None
  
          corner_opts = {
              "labels": sampler.labels,
              "truths": MLp,
              "quantiles": [0.16, 0.5, 0.84],
              "verbose": False,
              "truth_color": color_cycle[0],
          }
  
          corner_opts.update(kwargs)
  
          f = corner(sampler.flatchain, **corner_opts)
      except ImportError:
          log.warning(
              "The corner package is not installed;" " corner plot not available"
          )
          f = None
  
      plt.rcParams["lines.linewidth"] = oldlw
  
      return f